ObjectDetect: A Real-Time Object Detection Framework for Advanced Driver Assistant Systems Using YOLOv5
Wireless Communications and Mobile Computing (Wiley), 2022
A real-time multimodal object detection framework for Advanced Driver Assistance Systems (ADAS), integrating vision and LiDAR-based perception for robust environmental understanding. The system uses YOLOv5 for high-speed, high-accuracy detection, achieving about 95% accuracy while significantly improving inference speed compared to YOLOv3 and YOLOv4, and supports reliable object detection and tracking under real-world driving conditions.